| Summary: | Prostate cancer is the most common malignancy afflicting Canadian men in 2011. Physicians use digital rectal exams (DRE), blood tests for prostate specific antigen (PSA) and transrectal ultrasound (TRUS)-guided biopsies for the initial diagnosis of prostate cancer. None of these tests detail the spatial extent of prostate cancer - information critical for using new therapies that can target cancerous prostate. With an MRI technique called proton magnetic resonance spectroscopic imaging (1H-MRSI), biochemical analysis of the entire prostate can be done without the need for biopsy, providing detailed information beyond the non-specific changes in hardness felt by an experienced urologist in a DRE, the presence of PSA in blood, or the “blind-guidance” of TRUS-guided biopsy. A hindrance to acquiring high quality 1H-MRSI data comes from signal originating from fatty tissue surrounding prostate that tends to mask or distort signal from within the prostate, thus reducing the overall clinical usefulness of 1H-MRSI data. This thesis has three major areas of focus: 1) The development of an optimized 1H-MRSI technique, called conformal voxel magnetic resonance spectroscopy (CV-MRS), to deal the with removal of unwanted lipid contaminating artifacts at short and long echo times. 2) An in vivo human study to test the CV-MRS technique, including healthy volunteers and cancer patients scheduled for radical prostatectomy or radiation therapy. 3) A study to determine the efficacy of using the 1H-MRSI data for optimized radiation treatment planning using modern delivery techniques like intensity modulated radiation treatment. Data collected from the study using the optimized CV-MRS method show significantly reduced lipid contamination resulting in high quality spectra throughout the prostate. Combining the CV-MRS technique with spectral-spatial excitation further reduced lipid contamination and opened up the possibility of detecting metabolites with short T2 relaxation times. Results from the in vivo study were verified with post-histopathological data. Lastly, 1H-MRSI data was incorporated into the radiation treatment planning software and used to asses tumour control by escalating the radiation to prostate lesions that were identified by 1H-MRSI. In summary, this thesis demonstrates the clinical feasibility of using advanced spectroscopic imaging techniques for improved diagnosis and treatment of prostate cancer.
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